Adaptive Algorithm Selection

Adaptive selection aims to choose the option with greater performance or efficiency benefit relative to cost. The system may replace a poorly fitting algorithm pattern with another that provides better value. The system can compare alternative algorithm patterns under current observed conditions. Algorithm adaptation is constrained by both correctness checks and performance measurements. A new algorithm pattern should be adopted only if it still satisfies unit tests.